# Extremes

Meteonorm's default climate data represents a **median, average climate**, meaning
there's a **50% probability of exceedance (PoE 50)**. When generating hourly data, the
software typically uses PoE 50 monthly averages as its basis, ensuring that the
resulting hourly values reflect a typical distribution for that month, including
**typical hourly extremes** (e.g. average highest or lowest hourly temperatures).

However, you have the option to generate **extreme values** corresponding to **PoE 10**
and **PoE 90**.

- **PoE 10 (P10)**: This represents a scenario where only 10% of values of a parameter (e.g. yearly
  Global Horizontal Irradiance) are higher than the given one. In practical
  terms for Meteonorm, choosing PoE 10 for monthly averages of temperature and global
  irradiance will simulate a **warm month with high solar irradiance**.
- **PoE 90 (P90)**: Conversely, this means 90% of all values of a parameter are higher than the given
  one. In Meteonorm, selecting PoE 90 for monthly averages of temperature and global
  irradiance will simulate a **cold month with low solar irradiance**.

These extreme values (PoE 10 and PoE 90) apply to both **global irradiance and
temperature** together, and can be applied to both **monthly averages** and **yearly
averages**:

- **Yearly averages**: Applying PoE 10 or PoE 90 here means you are generating a year
  with a statistical probability of occurring once in a decade (e.g. the warmest or
  coldest year in a 10-year period).
- **Monthly averages**: If you apply PoE 10 or PoE 90 to monthly averages, it implies
  that every single month in the year corresponds to that extreme (e.g. every month is
  a PoE 10 warm month). This is a very strong assumption and statistically highly
  unlikely to happen in reality.

It is important to note that within the context of Meteonorm, "P" is used interchangeably
with "PoE" (Probability of Exceedance). This aligns with common usage in the solar and
wind power industries, which differs from a purely statistical context where "P"
typically refers to a percentile

Extremes can be selected by setting the `extreme_setting` query
parameter in the `/climate/tmy` endpoint.